A Tricycle Model to Accurately Control an Autonomous Racecar with Locked
Differential
- URL: http://arxiv.org/abs/2312.14808v1
- Date: Fri, 22 Dec 2023 16:29:55 GMT
- Title: A Tricycle Model to Accurately Control an Autonomous Racecar with Locked
Differential
- Authors: Ayoub Raji, Nicola Musiu, Alessandro Toschi, Francesco Prignoli,
Eugenio Mascaro, Pietro Musso, Francesco Amerotti, Alexander Liniger, Silvio
Sorrentino, Marko Bertogna
- Abstract summary: We present a novel formulation to model the effects of a locked differential on the lateral dynamics of an autonomous open-wheel racecar.
We include a micro-steps discretization approach to accurately linearize the dynamics and produce a prediction suitable for real-time implementation.
- Score: 71.53284767149685
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: In this paper, we present a novel formulation to model the effects of a
locked differential on the lateral dynamics of an autonomous open-wheel
racecar. The model is used in a Model Predictive Controller in which we
included a micro-steps discretization approach to accurately linearize the
dynamics and produce a prediction suitable for real-time implementation. The
stability analysis of the model is presented, as well as a brief description of
the overall planning and control scheme which includes an offline trajectory
generation pipeline, an online local speed profile planner, and a low-level
longitudinal controller. An improvement of the lateral path tracking is
demonstrated in preliminary experimental results that have been produced on a
Dallara AV-21 during the first Indy Autonomous Challenge event on the Monza F1
racetrack. Final adjustments and tuning have been performed in a high-fidelity
simulator demonstrating the effectiveness of the solution when performing close
to the tire limits.
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